______AJSW, Volume 10 Number 2 2020 AKASHRAJ D. P., GENG ATEM, K.K.G. & PANTH, A.S.

Publisher African Journal of Social Work Afri. j. soc. work © National Association of Social Workers-Zimbabwe/Author(s) ISSN Print 1563-3934 ISSN Online 2409-5605

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SOCIO-ECONOMIC PROFILE OF UNEMPLOYED POPULATION IN COUNTY: A STUDY IN SOUTH

AKASHRAJ, Devanga Pruthviraj.; GENG ATEM, Kom Kom and PANTH, Ananth S.

ABSTRACT

South Sudan as a nation has experienced several forms of economic, political and social unrest due to unemployment situation in the country. The Government has realized problem of unemployment especially the urban youth, and mitigate it through specific policy interventions. This paper attempts to support policy making in identifying the unemployed persons and knowing their profile. Information were obtained through a primary survey of 100 households with population size of 690 across five payam (sub-county) in Juba County. The results show that the unemployed members among the sample households are those with fairly large families with high dependency ratio and low literacy rate especially among the girls and women.

KEY TERMS: Unemployment, socio-economic profile, literacy, community, dependents, economic status, primary and secondary occupation, household assets, amenities, standard of living, Sudan

KEY DATES Received: 8 May 2020 Revised: 18 June 2020 Accepted: 01 August 2020 Published: 15 August 2020

Funding: None Conflict of Interest: None Permission: Not applicable Ethics approval: Not applicable

Author/s details: Dr Akashraj D. P, Associate Professor, Department of Economics, , South Sudan. Kom Kom Geng Atem, MSc Student, Department of Economics, University of Juba, South Sudan and Dr Ananth S Panth, Social Development Consultant Emails: [email protected], [email protected], and [email protected]

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INTRODUCTION

Globally, the number of young graduates is about to become the largest in history relative to the adult population. At present, more than 50 percent of the population is under the age of 25, or just over three billion individuals are youth or children (UNFP, 2000). In terms of youth alone there are over 1.3 billion youth in the world today. South Sudan as a nation has experienced several forms of economic, political and social unrest. In recent times, unemployment which is caused by government forces had joined the list of the social evils we experience in Juba today. The issue of unemployment has become a major phenomenon for South Sudanese demanding for increased attention. The problem of unemployment in South Sudan now has attracted of great concern is the South Sudan economists, policy makers, economic managers, individuals, government and many others. The Government realized that there was a need to deal with urban youth unemployment through specific Policy interventions. The development policy and the National Employment policy were published. Low investment and low economic growth rates are the issues that have contributed to unemployment. Juba is not able to attract the investment levels required and government is not investing enough in the areas of education, health, provision of water, electricity, security, and judicial services partly because of the constraints imposed by its development partners who impose restrictions on public expenditure as a condition for accessing financial support. The overall objective is to explore the unemployment situation across the different sections of the society in South Sudan. The specific objective is to highlight the socio- economic profile of unemployed population in Juba County and suggest measures to overcome unemployment.

BRIEF BACKGROUND

According to Bello (2003), the subject of unemployment has always been an issue of concern to the economists, policy makers and economic managers given the devastating on individuals, the society and the economy at large. The Keynesian revolution of the 1930’s, which commandeered the explosive attack on economic orthodoxy apparently, treated unemployment as a central issue of great concern. The International Labor Organization defined unemployment as the people who are out of work, want a job, have actively sought for work in the previous four weeks and are available to start work within the next fortnight (ILO, 2005). According to Juan Ramón (2011), graduate unemployment is an evidence of serious shortcomings in educational system and labor market in developing economy, which explains the country's relative high rate of youth unemployment and the imbalance between job supply and demand at the different educational levels attained. The gap that exists between the demand for and supply of university graduates in the South Sudan labor market is a serious issue due to prevailing high level of graduate unemployment. This has serious adverse social and economic consequences on the South Sudan economy (Atan et al, 2012). The demand for labor is derived from production and distribution activities in the goods and service sectors (Dabalen et al., 2000). The demand for labor in South Sudan economy has been poor and volatile Dabalen et al. (2010). According to Olufemi and Adebola (2011), both government and policy makers in South Sudan are increasingly finding it difficult to deal successfully with graduate unemployment.

METHODOLOGY

The analysis is based on primary source of data based on a household survey conducted in five selected payams (sub-county) namely Juba, Kator, Munuki, Rajaf, Gudele, belonging to Juba county in Central state of South Sudan (refer Maps indicating the study area). The total sample size is 100 households with 20 sample households in each payami. The total population of the sampled house hold is 690. The socio-economic profile of the sample households is analysed by categorizing the indicators into demographic profile, economic profile, social profile, and household assets & amenities. This research is a part of the project report submitted for the partial fulfilment of master’s degree. The data was collected by visiting the selected sample households and conducting personal interview with household heads. The data was obtained through the structured questionnaire, initially explaining the purpose of the study to the head of the household and obtaining their consent. The data from the primary survey was used for the purpose of this study only and not shared with any other individual or organization.

Figure 1: Map of the Study Area

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Demographic Profile

In South Sudan, the society consists of small size families as well as large size families. There are both social and economic reasons that motivate to have large size families in under developed and developing countries. In the sample there are small size families with one to three members to a maximum of 16 members, though low in proportion. The total population size across the 100 households is 690 members, shown in Table 1 and graph 1, giving an average family size of seven persons. At the aggregate, 37 per cent of the sample households have smaller families with one to five members. A significantly higher proportion accounting for 56 per cent of total sample, the sample households have a family size of six to 10 members. Only a smaller proportion accounting for seven percent have large families with 11 to 16 members.

Table 1: Total Number of Family Members in Sample Households

Payam / Taluk 1-5 6-10 11-16 Grand Total Gudele 1 19 0 20 Juba 5 15 0 20 Kator 20 0 0 20 Munuki 2 13 5 20 Rajaf 9 9 2 20 Grand Total 37 56 7 100

The sample household members were in the age group of less than one year to 79 years (refer Table 2). Across the various age groups, children of less than 10 years account for 18.7 per cent. The adolescent group account for 15.2 per cent. The youth account for 48.4 per cent and the peak working group account for 14.8 per cent. The senior citizens account for 2.9 per cent. Thus, the youth account for maximum and significant proportion and the aged population is comparatively insignificant. Across gender, at the aggregate, there is a significant disproportion in the ratio with 60 per cent male and 40 per cent female population. This disparity is maximum in the age group of 19-35 years with 66 per cent male and 34 per cent female. In case of the adolescent group, the sex ratio is fairly better with 54 and 46 per cent. Among children of less than 10 years, the sex ratio is 55 per cent of female and 45 per cent male. It is a point to ponder as to how the sex ratio reverses over a period of time. It is inferred that there is a sizable proportion of population with high scope for employment.

Table 2. Distribution of Sample Household Members by Age Group and Gender

Age Group Female Male Grand Total Upt o 10 71 58 129 % 55.04 44.96 100.00 11-18 48 57 105 % 45.71 54.29 100.00 19-35 114 220 334 % 34.13 65.87 100.00 36-60 43 59 102

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% 42.16 57.84 100.00 61-80 6 14 20 % 30.00 70.00 100.00 Grand Total 282 408 690 % 40.87 59.13 100.00

Dependency ratio, which can be defined as the ratio of number of non-workers to the total members, reflects to an extent the well-being of a family. It is inversely proportion, i.e. lower the dependency ratio higher would be the wellbeing, though there are other factors that determine. According to the World Bank sources, the dependency ratio of South Sudan is 83 per cent as compared to the world aggregate of 54 per cent. The World Bank categorizes countries with high dependency ratio of around 85 per cent as low-income countries and heavily indebted poor countriesii . Similarly, 29 families have five to six dependents, followed by 17 families and 14 families with three to four members and seven to eight members respectively. Only one household had one to two dependents. There are about 62 types of communities in South Sudan. Of them, the sample households belong to mainly four communities namely Dinka, Nuer, Azande and Bari that account for 60 per cent of total households. Remaining 40 per cent of them belong to other communities. Table 3 and graph 2 shows payam wise details of the communities to which they belong to.

Table 3: Distribution of the Sample Households by Community

Payam / Taluka Dinka Nuer Azande Bari Others Grand Total Gudele 20 0 0 0 0 20 Juba 4 0 0 2 11 20 Kator 3 1 1 7 8 20 Munuki 12 1 1 0 6 20 Rajaf 3 0 1 2 14 20 Grand Total 42 2 6 11 39 100

Figure 2: Community profile

Dinka 150 Nuer 100 Azande 50 Bari 0 Others Gudele Juba Kator Munuki Rajaf Total

The sample households belong to mainly two religions i.e. Islam and Christianity, accounting for eight per cent and 92 per cent respectively. The households belonging to Islam religion were in two payam namely Kator and Rajaf.

Social Profile

The primary data in Table 3, shows that at aggregate, 64 per cent of the household members are literate. Across gender, male literacy is higher accounting for around 70 per cent compared to 30 per cent of female literacy (refer graph 3). Thus, we observe that there is a very high disparity of over two and half times, in the literacy level across the gender. The gender disparity in illiteracy is however, comparatively lesser. Among the literates, comparatively higher proportions of the sample household members are school students and college graduation students (refer Table 4). As per the Table there is a very high gender disparity in the educational status with more male students as compared to the female students in the middle school, high school and university education. The disparity is fairly lesser in primary school education.

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We infer that there is a significantly high gender disparity in the literacy rates with more male students as compared to female students at all levels except the primary school level. thus showing that there is a drop out of girl children from schooling from primary level to high school and higher education also. However, across the gender, the proportion in higher education is fairly low. Similarly, number of persons in vocational studies is also negligible. These have direct impact and consequences on their employability in particular and overall employment situation in the country, in general.

Table 4: Distribution of Sample Household Members by Status of Literacy

Status Female Male Grand Total Illiterate 147 99 246 % 59.76 40.24 100.00 Literate 135 309 444 % 30.41 69.59 100.00 Grand Total 282 408 690 % 40.87 59.13 100.00

Economic Profile

The economic profile of the households is analysed with income represented by APL/BPL status; and employment represented by engagement in primary and secondary occupation. Table 5 provides the economic status of sample households. At the aggregate, 46 per cent households have BPL status and remaining 54 per cent have APL status. Across the sample payam, the BPL households are concentrated in Munuki and Rajaf payam. Whereas, the APL households are in Kator, Gudele and Juba payam. In Munuki and Rajaf payam, the BPL status of households are also those with unemployment of more than 25 per cent in the family. We infer that there is no significant correlation between economic status of the family.

Table 5. Distribution of Sample Households by Economic Status

Payam / Taluka BPL APL Grand Total Gudele 5 15 20 Juba 7 13 20 Kator 1 19 20 Munuki 17 3 20 Rajaf 16 4 20 Grand Total 46 54 100

Figure 3: Economic status

100 80 60 BPL 40 APL 20 0 Gudele Juba Kator Munuki Rajaf Grand Total

The employment pattern of the sample household members shown in Table 6 that at the aggregate is around 20 percent of the sample household members had gainful primary occupation and 10 per cent of them had secondary occupation. As per the demographic profile, around 37 per cent are below age of 18 years and above 60 years. Hence in all 63 per cent of the sample households are in the working age group. Hence there is a very significant

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______AJSW, Volume 10 Number 2 2020 AKASHRAJ D. P., GENG ATEM, K.K.G. & PANTH, A.S. gap of 44 per cent, between the number of persons employable and those who are employed. Among the members with primary occupation, 36 per cent were civil servants, followed by casual workers (24%) and farming (17%). There were also other professions such as teachers, traders and craftsmen, but, account for small proportion. About 10 per cent were occupied in various other trades. Similarly, in the secondary occupation, among the active workers, 32 per cent were into farming. 19 per cent were civil servants, 16 per cent livestock breeders. This shows that there is sufficient scope for people to be employed in several other trades and obtain incomes.

Table 6: Distribution of Sample Household Members by Primary Occupation and Gender

Occupation Female % Male % Grand Total % Farmer 10 43.48 13 56.52 23 3.33 Livestock breeder 0 0.00 1 100.00 1 0.14 Retired 0 0.00 2 100.00 2 0.29 Craftsman 0 0.00 5 100.00 5 0.72 Merchant 1 25.00 3 75.00 4 0.58 Civil Servant 9 18.37 40 81.63 49 7.10 Worker 13 40.63 19 59.38 32 4.64 Teacher 1 20.00 4 80.00 5 0.72 Doctor 0 0.00 1 100.00 1 0.14 Other 4 28.57 10 71.43 14 2.03 Not Applicable 237 44.13 300 55.87 537 77.83 I do not Know 8 47.06 9 52.94 17 2.46 Motor 0 0.00 1 100.00 1 0.14 Grand Total 283 41.01 407 58.99 690 100.00

Household Assets and Amenities

The household profile of sample households includes the type of house, ownership status, size of the house in terms of number of rooms and type of construction of the house. As described in Table 7, house is categorised into five types namely hut, semi-pucca, pucca, apartment and bungalow. At the aggregate, 22 per cent live in hut, 37 per cent in semi-pucca houses, 16 per cent in pucca houses and 24 per cent live in independent houses. Information on the ownership status shows that at aggregate, 66 per cent live in own houses and 28 per cent households live in rented houses. The sample households, accounting for three per cent of total, who are living in houses provided by their employer. Similarly, very few households accounting for two per cent of total are living in houses where it has been provided rent free to them.

Analysing the ownership status by type of house in Table 8, shows that in Gudele payam 80 per cent of the households living in own houses are independent bungalows. In other four payam, the households with own or rented houses are living either in huts or semi-pucca houses (refer graph 5). Overall, we may infer that the sample households with APL status live in pucca and independent houses. Similarly, the households with BPL status live in huts and semi-pucca houses. Hence there is a correlation between economic status of the household and the type of house they live.

Table 7: Distribution of Sample Households by Type of House

Payam Hut Semi Pucca Pucca Apartment Independent House Grand Total Gudele 0 1 2 1 16 20 Juba 8 5 7 0 0 20 Kator 2 16 2 0 0 20 Munuki 8 5 1 0 6 20 Rajaf 4 10 4 0 2 20 Grand Total 22 37 16 1 24 100 Table 8: Distribution of Sample Households by Status of Ownership of Present Residence

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Payam Own Rented Given by Employer Not Paying Rent Others Grand Total Gudele 20 0 0 0 0 20 Juba 12 7 1 0 0 20 Kator 6 11 1 2 0 20 Munuki 15 4 0 0 1 20 Rajaf 13 6 0 1 0 20 Grand Total 66 28 2 3 1 100

The sources of domestic water supply found during survey were water pump, well water and water tank as shown in Table 9. The household’s data reveals that at the aggregate 94 per cent of the households obtain water from water tank, five per cent of them from water pump and one per cent from well water. None of the sample houses had tap water connections inside their house or even outside their house.

Table 8: Distribution of Households by Source of Domestic Water Supply in the House

Plumbing inside Payam the house Water pump Well water Water tank Grand Total Gudele 0 1 1 18 20 Juba 0 1 0 19 20 Kator 0 1 0 19 20 Munuki 0 2 0 18 20 Rajaf 0 0 0 20 20 Grand Total 0 5 1 94 100

Standard of Living

The standard of living of the sample households has also been considered in the study through indicators including type of fuel used for cooking, movable assets such as television set, use of cable / dish antenna, radio, access to newspaper and magazines, and internet connection. Among the sample households, 77 per cent use firewood for cooking and 21 per cent use other sources of fuel that include charcoal and electric stove (refer Table 10). Across the sample payam, only one per cent household use LPG in Kator payam and one per cent in Gudele use kerosene as fuel for cooking. There is no bio-fuel used in any of the sample households. Thus, it is inferred that households use firewood as fuel for cooking irrespective of economic status.

Table 9. Distribution of Sample Households by Type of Cooking Fuel Used

Payam LPG Kerosene Firewood Bio-Fuel Others Grand Total Gudele 0 1 19 0 0 20 Juba 0 0 16 0 4 20 Kator 1 0 17 0 2 20 Munuki 0 0 5 0 15 20 Rajaf 0 0 20 0 0 20 Grand Total 1 1 77 0 21 100

CONCLUSIONS

The article is an attempt to highlight the high levels of unemployment in South Sudan in general and state in particular. The focus of the article is to identify the segment of the society who are unemployed

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______AJSW, Volume 10 Number 2 2020 AKASHRAJ D. P., GENG ATEM, K.K.G. & PANTH, A.S. and highlight their socio-economic profile. The socio-economic profile of the sample households is analysed by categorizing the indicators into demographic profile, economic profile, social profile, and household assets & amenities. The analysis is based on primary source of data based on a household survey in five selected payams with 20 households in each payam, with total sample of 100 households. The analysis reveals that in the demographic profile, the family size varies from single person to 16 person per family with an average of 6.90 i.e. seven persons per family for the total sample. Though large family size is preferable to have a greater number of persons who are employable. However, in this case we have not observed such phenomena. The gender profile shows high disparity in sex ratio especially in age groups above 19 years. It is comparatively lower in adolescent group and young children of less than 10 years. The dependency ratio of in sample family varied from 26 per cent to over 75 per cent. There is a positive relation of dependency ratio with proportion of unemployed in the family. The sample households belong to mainly four communities namely Dinka, Nuer, Azande And Bari. 92 per cent of them are Christians and eight per cent are Muslims. Literacy profile shows that there are 64 per cent literates, but male literacy is more than twice the female literacy. The literacy status of the sample household members shows that the members have completed / currently enrolled in schooling and graduation. The proportion of persons in vocational training and post-graduation is negligible. Hence there is scope for enrollment in higher education and vocational training as it increases employability. The economic profile of the sample household members shows that 46 per cent belong to below poverty line status and 54 per cent belong to above poverty line status. There is no significant correlation between economic status and unemployment status of the family. The occupation of the household members shows that out of total 690 members only 20 per cent had primary source of employment and nine per cent had secondary sources of employment. From the Table on demographic profile, we observe that the proportion of children below 18 years account for 37 per cent of total household members. So, the percentage of persons who can be actively employed is around 63 per cent as compared to 20 per cent in primary activity and 10 per cent in secondary activity. Hence there is high level of employment among household members. The high unemployed proportion is mainly due to low levels of literacy i.e. graduates, schooling and vocational training. There is also a significant incidence of drop out of girl children from education at all levels. The household assets and amenities profile of households shows that 60 per cent live in huts and semi-pucca houses. 94 per cent obtain water from water tanks and only five percent from water pumps. No households have piped water connections as most of them live in huts and semi-pucca houses. Thus, due to low incomes arising out of high level of unemployment in the family (with both APL and BPL status) is resulting in the housing to be in very poor condition. On the standard of living, 77 per cent use firewood as fuel for cooking and use of LPG is negligible and bio- fuel is non-existent. Hence it is inferred that households are not in a position to afford LPG for cooking. Only 12 per cent purchase newspaper and nine per cent purchase magazines. 52 per cent of the sample households possess a television set of which 27 per cent is colour set and 25 per cent have black & white TV sets. Only 34 per cent of them have access to DTH connection. This could be partially due to economic status and infrastructure too. Hence there is ample scope for employment in providing these services. Though there is a radio at home among 73 per cent of the sample, only five per cent of them have access to internet connection which calls for employment opportunity. Similar to the housing condition, the people both with APL and BPL status are not in a position to afford items such as LPG for cooking, purchase of newspaper and possession of TV sets and access to internet connection. In all, the socio-economic condition of families in Juba county is very poor, irrespective of the community they belong to or the economic status as observed through indicators of economic profile, social profile, and household assets & amenities.

RECOMMENDATIONS

Based on the analysis carried out on the socio-economic indicators we would like to make suggestions for the improvement of the lives of the people in Juba county and for the whole of Central Equitoria in general. Government must facilitate more enrollment in university for level master degree education. Government and civil society must promote education of girl child in high school, graduation, and master degree levels. Government and philanthropic organisations must initiate to provide stipend to graduates and post graduate students as it will not be hindrance for them from not studying due to high tuition fees. Business sector and University must jointly promote earn while you learn schemes, where students can earn and pay for their education. This will improve their responsibility. Government must promote vocational training such as industrial training institutes and polytechnic institutes in several trades, amongst youth to make them employable.

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REFERENCES

Atan, J. (2012). Labour Market Distortions and University Graduate Unemployment in Nigeria. Current Research Journal of Economic theory, 4(3), 67-76. Atan et al, (2012). Graduate Turn-out and Graduate Unemployment in Nigeria, International Journal of Humanities and Social Sciences, 2(14), 38-46. Awogbenle, A. and K. (2010). Youth Unemployment; Entrepreneurship Development Programme as an intervention mechanism, African Journal of Business Management, 4(6), 831-835. Bello. J. (2011). Graduate Unemployment and Criminality in Ado-Ekiti, International Journal of Business Resources Management, 5(1), 61-77. Brue, K. (2007). Adopting a constructivist approach to employment theory: Implications for research design. International Journal of employment Practice, 6(2), 98-105. Campbell, M. (2011). Mamboing in qualitative research: Probing data and processes of employment, 3(5), 40-50. Dabalen et al, (2000). Graduate Unemployment in Ghana Possible Case of Poor Response of University Programme to the Demand of the Job Market: Report of the Educational Research Network for West Africa and Central Africa, 1(4), 60-70. Dabalen, A., (2000). Labour Market Prospects for University Graduates in Sudan. Higher Education Management, 14(1), 1-36. Danjos, D & Ali, S. (2014). Implications of Unemployment in Gabon’s Sustainable Development, International Journal of Public Administration and Management Research, 2(2), 56-65. Davidson. (2010). Challenges of employment in Africa: a new approach uncovers their value. Journal of employment practice, 3(2), 66-75. Essien, E. & Ekpo, N. (2012). Is Ghana Unemployment Problem Unsolvable? Current Research Journal of Social Sciences, 4(6), 389-395. Fajana. A. (2000); Reducing Graduate Unemployment through Entrepreneurship Development. The Nigerian Experience, African Journal of Social Sciences, 2(4), 139-152. Fisher, A. (2011). People perception of unemployment in Africa and the way to combat unemployment in Africa youth population. Practice, 3(2), 66-75. Godwin. A. and Aderonmu, O. (2015). Assessment of Entrepreneurship Education and Employment Generation among University Graduates in Kenya; European Journal of Business and Management, 7(23), 136-143. International Labor Organization (ILO, 2012). Global Employment Trends for Youth, Switzerland. Retrieved Jan 3 2014 http://wwwilo.org/or (msp5/groups/public/-- dgreputi/dcomm/document/publication/wcms 180976 PDF. John, K. (2002); Unemployment in Africa Paper Presented at African Transformation Forum organized by African Centre for Economic Transformation (ACET), April, 2016, Kigali, Rwanda. Practice, 3(2), 66-75. Johnson, M. (2013); Graduate Unemployment in Nigeria. Entrepreneurship and Venture capital Nexus. Journal of Economic and Sustainable Development, 4(9), 75-81. Keynes, M., E. (2006). Ameliorating the Problem of Unemployment among Graduates through Relevant Functional and Sustainable University Education in South Africa: International Review of Social Sciences and Humanities, 7(2), 188-196. Komba. J. (2007). Satisfaction, sacrifice, surprise: three small steps create one giant leap into the experience economy and improvement in the employment sector, 3(2), 66-75. Madoui, M. (2015); Unemployment among Young Graduates in Algeria: A Sociological Reading; Open Journal of Social Sciences, 3(1), 35-41. Olufemi, S. (2011). Socio-Economic Impact of Graduate Unemployment in Tanzania and the Vision 20: 2020, International Journal of Development and Sustainability, 2(1), 148-176. Ramon, I. (2008). Reducing Unemployment through the Informal Sector a case study of Nigeria. European Journal of Economics, Finance and Administrative Science, 1(1), 97-106. Shapiro, O. (2004). Youth Unemployment and its Socio-Economic Implications in Uganda. Journal of social sciences and public policy, 4(1), 49-57. Turunen, T. (2008). Human Resources Planning in Tanzania. The National Directorate of Employment and Youth Unemployment. The Tanzania Journal of Industrial Education and Labour Relations, 6(2), 167-180. William, A. (2006); Education, Poverty and Development UNESCO. International Institute for Education and Development Ghana, Possible Case of Poor Response of University programs to the Demand of job Market. Research Paper Series, 5(3), 6-7.

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